#!/usr/bin/env python3 """ Generate TTS audio files for recording commentary using OpenAI's API. Usage: python scripts/recording_audio.py path/to/recording.md """ import argparse import os import re import sys from pathlib import Path import requests from dotenv import load_dotenv # Load environment variables from .env file load_dotenv() # Configuration OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY") OUTPUT_DIR = "aider/website/assets/audio" VOICE = "onyx" # Options: alloy, echo, fable, onyx, nova, shimmer def extract_recording_id(markdown_file): """Extract recording ID from the markdown file path.""" return Path(markdown_file).stem def extract_commentary(markdown_file): """Extract commentary markers from markdown file.""" with open(markdown_file, "r") as f: content = f.read() # Find Commentary section commentary_match = re.search(r"## Commentary\s+(.*?)(?=##|\Z)", content, re.DOTALL) if not commentary_match: print(f"No Commentary section found in {markdown_file}") return [] commentary = commentary_match.group(1).strip() # Extract timestamp-message pairs markers = [] for line in commentary.split("\n"): line = line.strip() if line.startswith("- "): line = line[2:] # Remove the list marker match = re.match(r"(\d+):(\d+)\s+(.*)", line) if match: minutes, seconds, message = match.groups() time_in_seconds = int(minutes) * 60 + int(seconds) markers.append((time_in_seconds, message)) return markers def generate_audio_openai(text, output_file, voice=VOICE): """Generate audio using OpenAI TTS API.""" if not OPENAI_API_KEY: print("Error: OPENAI_API_KEY environment variable not set") return False url = "https://api.openai.com/v1/audio/speech" headers = {"Authorization": f"Bearer {OPENAI_API_KEY}", "Content-Type": "application/json"} data = {"model": "tts-1", "input": text, "voice": voice} try: response = requests.post(url, headers=headers, json=data) if response.status_code == 200: with open(output_file, "wb") as f: f.write(response.content) return True else: print(f"Error: {response.status_code}, {response.text}") return False except Exception as e: print(f"Exception during API call: {e}") return False def main(): parser = argparse.ArgumentParser(description="Generate TTS audio for recording commentary.") parser.add_argument("markdown_file", help="Path to the recording markdown file") parser.add_argument("--voice", default=VOICE, help=f"OpenAI voice to use (default: {VOICE})") parser.add_argument( "--output-dir", default=OUTPUT_DIR, help=f"Output directory (default: {OUTPUT_DIR})" ) parser.add_argument( "--dry-run", action="store_true", help="Print what would be done without generating audio" ) args = parser.parse_args() # Use args.voice directly instead of modifying global VOICE selected_voice = args.voice recording_id = extract_recording_id(args.markdown_file) print(f"Processing recording: {recording_id}") # Create output directory output_dir = os.path.join(args.output_dir, recording_id) if not args.dry_run: os.makedirs(output_dir, exist_ok=True) # Extract commentary markers markers = extract_commentary(args.markdown_file) if not markers: print("No commentary markers found!") return print(f"Found {len(markers)} commentary markers") # Generate audio for each marker for time_sec, message in markers: minutes = time_sec // 60 seconds = time_sec % 60 timestamp = f"{minutes:02d}-{seconds:02d}" filename = f"{timestamp}.mp3" output_file = os.path.join(output_dir, filename) print(f"Marker at {minutes}:{seconds:02d} - {message}") if args.dry_run: print(f" Would generate: {output_file}") else: print(f" Generating: {output_file}") success = generate_audio_openai(message, output_file, voice=selected_voice) if success: print(f" ✓ Generated audio file") else: print(f" ✗ Failed to generate audio") if __name__ == "__main__": main()